Title :
An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation
Author :
Yu, Shimeng ; Wu, Yi ; Jeyasingh, Rakesh ; Kuzum, Duygu ; Wong, H. -S Philip
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
The multilevel capability of metal oxide resistive switching memory was explored for the potential use as a single-element electronic synapse device. TiN/HfOx/AlOx/ Pt resistive switching cells were fabricated. Multilevel resistance states were obtained by varying the programming voltage amplitudes during the pulse cycling. The cell conductance could be continuously increased or decreased from cycle to cycle, and about 105 endurance cycles were obtained. Nominal energy consumption per operation is in the subpicojoule range with a maximum measured value of 6 pJ. This low energy consumption is attractive for the large-scale hardware implementation of neuromorphic computing and brain simulation. The property of gradual resistance change by pulse amplitudes was exploited to demonstrate the spike-timing-dependent plasticity learning rule, suggesting that metal oxide memory can potentially be used as an electronic synapse device for the emerging neuromorphic computation system.
Keywords :
CMOS integrated circuits; brain models; neural nets; brain simulation; cell conductance; metal oxide resistive switching memory; multilevel resistance states; neuromorphic computation system; neuromorphic computing; nominal energy consumption; programming voltage amplitudes; pulse amplitudes; pulse cycling; resistive switching cells; single-element electronic synapse device; spike-timing-dependent plasticity learning rule; subpicojoule range; Energy consumption; Immune system; Metals; Neurons; Resistance; Switches; Bio-inspired system; neuromorphic computation; resistive switching memory; spike-timing-dependent plasticity (STDP); synapse;
Journal_Title :
Electron Devices, IEEE Transactions on
DOI :
10.1109/TED.2011.2147791